Primary Questions Are

Assessing Data Coverage and Completeness

We are interested in the distribution of farm characteristics at the subnational level. To assess a “distribution”, we would need a sufficient number of households.

Based on the plots above, there are three candidates from the datasets which have helpful characteristics:

  1. They have a relatively large number of surveys (n>2000)
  2. They have surveys in a significant portion of their subnational areas (>40%)

The three countries are Burkina Faso (West Africa), Rwanda (Central Africa), and Tanzania (East Africa).

Land Size

In this study, we are interested in looking at Land Size. Land size is an interesting variable to look at for smallholder farmers. It can tell us a lot about other variables (some of which are more error prone, or more difficult to measure e.g. income and food security).

Here we see that there might be some relationship between land size and total income, food security, and livestock holdings.

Interestingly we see that the spread varies for different quantiles. For example, for higher land sizes, we see a larger spread in income values.

Spread of Land Sizes

In mapping efforts, we often see researchers trying to map averages. For example, in the Lowder article, they mapped average farm size per subnational unit using census information, and information on the total arable land.

In different areas however, there is a large variation in land sizes. Here we see that we have a wide range of land size distributions, each of which vary quite significantly by country.

If we were to use land size to prioritise development interventions, it would be important to account for the characteristics of land size distributions.

Here we see that as the mean land size increases increases, so does the standard deviation (same goes for the median and IQR).

We also see that for most subnational areas, Land Size distributions are skewed, and in many of these areas the distributions are fat-tailed (normal distribution has kurtosis of ~ 3)

What does this mean in practice. Lets say we are using Land Size to target funding towards the poorest of the poor.

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Subnational Level Covariates